Jun 1, 2015 · We introduce two Python frameworks to train neural networks on large datasets: Blocks and Fuel. Blocks is based on Theano, a linear algebra compiler with CUDA- ...
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PDF | We introduce two Python frameworks to train neural networks on large datasets: Blocks and Fuel. Blocks is based on Theano, a linear algebra.
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Abstract: We introduce two Python frameworks to train neural networks on large datasets: Blocks and Fuel. Blocks is based on Theano, a linear algebra ...
This work introduces two Python frameworks to train neural networks on large datasets: Blocks and Fuel, which provides a standard format for machine learning ...
Jun 1, 2015 · Blocks relies on Fuel for its data interface, but Fuel can easily be used by other machine learning frameworks that interface with datasets. 3.1 ...
In my mind the big win for blocks is how they handle recurrence, its much easier to write code for a new RNN compared to some other theano based packages (or ...
Bibliographic details on Blocks and Fuel: Frameworks for deep learning.
Sep 13, 2019 · Tensorflow, Keras, Pytorch are popular deep learning frameworks. There are many other frameworks like Caffe, cntk. Essentially all these are ...
Deep learning (DL) frameworks offer building blocks for designing, training, and validating deep neural networks through a high-level programming interface.
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Jan 28, 2021 · 1. Blocks. Blocks is a framework that helps you build neural network models on top of Theano. Currently, it supports and provides, constructing ...